This disclosure relates generally to the field of digital photography. More particularly, but not by way of limitation, it relates to techniques for improved stabilization of video frames captured in low light conditions by taking into account motion blur within the video frames.
A standard rule of thumb for capturing sharp, handheld imagery is that the camera's shutter speed should not be less than its shutter speed equivalent to the focal length of the lens. This rule holds that a 500 millimeter (mm) lens shouldn't be handheld at shutter speeds slower than 1/500-second, a 300 mm lens slower than 1/300-second, a 50 mm lens slower than 1/50-second, and a 20 mm lens slower than 1/20-second.
With the application of software- and/or hardware-based stabilization technology, jitter caused by camera movement may be minimized, making it possible to transform shaky, handheld footage into steady, smooth shots. One way to stabilize a video is to track a salient feature in the image and use this as an anchor point to cancel out all perturbations relative to it. This approach requires a priori knowledge of the image's content to, for example, identify and track a person or other salient object in the scene. Another approach to image stabilization searches for a “background plane” in a video sequence, and uses its observed distortion to correct for camera motion. In yet another approach, gyroscopically controlled electromagnets shift a floating lens element orthogonally to the optical axis along the horizontal and vertical plane of the image in a direction that is opposite that of the camera movement. Doing this can effectively neutralize any sign of camera shake. In a similar type of operation, a camera's imaging sensor is translated in the opposite direction of the camera's movements in order to dampen the effects of camera shake.
One limitation of current video stabilization techniques is that they do not do a good job of accounting for so-called “motion blur” occurring in images, e.g., due to the user's hand shaking during video capture. “Motion blur” may be defined as the apparent “streaking” of rapidly moving pixels in a still image or a sequence of images. Motion blur results when the composition of the image being recorded changes during the recording of a single frame, either due to rapid movement (of the camera or objects in the scene being captured) or long exposure, i.e., integration, times.
The difficulties associated with stabilizing video frames exhibiting motion blur are further exacerbated in low light conditions due to the increased integration times needed to capture sufficient light in the recorded video frames. Longer integration times result in more motion blur in the recorded video frame. When such “low light” video is stabilized, the residual motion blur and associated “shimmering artifacts” often appear visible in the stabilized video. This may make the stabilized videos look unnatural and does not provide the user with the perceptual clues of video movement that would normally be associated with the presence of motion blur within a video frame.
Thus, what is needed are techniques to modulate the video stabilization strength parameter used to stabilize particular recorded video frames in a sequence of captured frames based, at least in part, on an estimated amount of motion blur in the particular video frame. Such techniques are also preferably power efficient and computationally efficient.